Color information of an image captured by an imaging apparatus is generated based on light entered into the imaging apparatus, the light being the environmental illumination light reflected by the surface of an object at the time of capturing the image. Therefore, when someone captures images of different objects each having the same surface reflectance under the different environmental illumination light, the color information of the captured images of the objects also vary. In such a technique that the object in a captured scene is recognized with the aid of a shape of the observed spectrum using a multispectral image in which light of multiple wavelengths is recorded, it becomes hard to identify the object if the observed spectrum varies according to a change of the environmental illumination light even in the same object. To solve the above problem, it is essential to obtain a surface reflectance of the object from the observed spectrum after eliminating the influence of the environmental illumination light from the observed spectrum. In other words, it is required to separate the spectral characteristic of the illumination and the spectral characteristic of the object from the observed spectrum to restore them.
There is a method for automatically estimating a spectral distribution of an illumination and a surface reflectance of an object in a captured scene with the aid of color information observed from the scene of, for example, an image. As an example of the method, such a method has been proposed that, on the assumption about an object color or an illumination color in the scene, the spectral characteristics of the illumination and the object are estimated with the aid of the assumption.
For example, in a method disclosed in Patent Literature 1, it is assumed that environmental illumination light is white, an average value of a reflectance is gray, and a visual characteristic of a person naturally supplies a color based on information around an edge area. In this method, each of the spectral distribution of the illumination and the surface reflectance of the object is represented by the linear sum of the preliminary stored principal component vector and mean vector, and energy to be required for satisfying the assumption is defined to be optimized. This ensures estimation of the spectral distribution of the illumination and the surface reflectance of the object.
Further, in a method disclosed in Patent Literature 2, on the assumption that a wide area is occupied by a skin-color object or a gray-color object in a captured image, an illumination range is corresponded to points on a black body locus, and, while changing the color temperature thereof, the energy required for satisfying the assumption is calculated and optimized, thereby estimating the color temperature. The color temperature estimated by the method ensures the estimation of illumination.
A schematic diagram of a method for estimating the illumination/reflectance using the above related art is shown in FIG. 11. The schematic diagram of FIG. 11 is a block diagram generated based on Patent Literature 1 and Patent Literature 2. Each of the above related art includes a color information acquiring means 1, an illumination/reflectance principal component vector storage memory 2, and a spectrum estimating means 3.
The color information acquiring means 1 acquires color information from a scene to output the acquired color information. The illumination/reflectance principal component vector storage memory 2 stores a principal component vector and a mean vector in order to represent constraints on a spectral distribution of an illumination and a surface reflectance of an object. The spectrum estimating means 3 calculates energy necessary for satisfying the assumption about an object color or an illumination color set in advance while each of the spectral distribution of the illumination and the surface reflectance of the object is represented by a linear sum of the respective principal component vector and mean vector using color information and optimizes the calculated energy. Further, the spectrum estimating means 3 outputs as estimated values the spectral distribution of the illumination and the surface reflectance of the object when the calculated energy becomes optimum.